|Year : 2017 | Volume
| Issue : 2 | Page : 87-95
A comparative study of psychosocial factors of obesity
Urbi Mukherjee1, Bidita Bhattacharya2, Shikha Mukhopadhyay3, Shuvabrata Poddar4
1 Department of Psychology, Dr. APJ Abdul Kalam Government Degree College, West Bengal State University, Kolkata, West Bengal, India
2 Department of Clinical Psychology, Institute of Psychiatry, Kazi Nazrul University, Asansol, West Bengal, India
3 Department of Psychiatry, Institute of Psychiatry, Kazi Nazrul University, Asansol, West Bengal, India
4 Department of Applied Psychology, Kazi Nazrul University, Asansol, West Bengal, India
|Date of Web Publication||26-Jul-2017|
Department of Psychology, Dr. APJ Abdul Kalam Government Degree College, West Bengal State University, 132, APC Road, Kolkata - 700 009, West Bengal
Source of Support: None, Conflict of Interest: None
Aims: The present study aims to find out how obese adults differ from nonobese adults with respect to self-concept, various domains of family environment, and general well-being. Subjects and Methods: A sample of sixty individuals within age group 21–50 years, selected using purposive sampling from obesity and lifestyle clinic of a hospital, was divided into obese and nonobese groups on the basis of body mass index (BMI) (≥25 kg/m2), with thirty individuals in each group. The sample was assessed on the basis of Self-concept Inventory (Shah, 1986), Family Environment Scale (Bhatia and Chadha, 1993), and General Health Questionnaire-28 (GHQ-28; Goldberg and Miller, 1979). Statistical Analyses: Statistical analyses included descriptive statistics, Student's t-test, Chi-square test, and correlational analysis. Results: Results showed statistically significant differences between the obese and nonobese individuals with respect to various domains of self-concept, family environment, and general well-being. Significant gender differences were found among the obese group with respect to different variables. Significant correlations between BMI and the different variables were also found. Conclusions: The findings imply several significant psychological and social issues associated with obesity in comparison to nonobese individuals. This underscores the need for nonmedical interventions (along with medical ones) for risk minimization and prevention.
Keywords: Body mass index, family, obesity, self-concept, well-being
|How to cite this article:|
Mukherjee U, Bhattacharya B, Mukhopadhyay S, Poddar S. A comparative study of psychosocial factors of obesity. Int J Educ Psychol Res 2017;3:87-95
|How to cite this URL:|
Mukherjee U, Bhattacharya B, Mukhopadhyay S, Poddar S. A comparative study of psychosocial factors of obesity. Int J Educ Psychol Res [serial online] 2017 [cited 2018 Feb 25];3:87-95. Available from: http://www.ijeprjournal.org/text.asp?2017/3/2/87/211643
| Introduction|| |
Over the past 40 years, obesity has been increasing at an alarming rate throughout the world with diverse patterns across nations and ethnic populations. It is a complex, multifactorial disease that develops from the interaction between genotype and the environment. Researchers found that obesity was the sixth most important risk factor contributing to the overall burden of disease worldwide. The World Health Organization (WHO) definition of overweight and obesity denotes abnormal or excessive fat accumulation that may impair health. The Centers for Disease Control define overweight and obesity as “labels for ranges of weight that are greater than what is generally considered healthy for a given height.”
Broadly, obesity is classified into primary and secondary. Primary obesity happens when a person consumes more kilojoules than the body can utilize and accounts for approximately 95% of obesity cases. Secondary obesity occurs as a consequence of some disease and which disappears after the disease has been cured.
The most widely used definitions of obesity are based on body mass index (BMI), which is calculated as weight in kilograms divided by the square of height in meters (kg/m 2). A BMI of 30 kg/m 2 is widely recognized as a cutoff point for obesity. Given, the small body frame of Indians and other Asians, data suggest that the proposed cutoffs by the WHO for defining overweight and obesity are not appropriate for Asian Indians and that they are at risk of developing obesity-related comorbidities at lower levels of BMI and waist circumference. The Indian Ministry of Health and Family Welfare proposed new obesity guidelines, which, in light of the particularly susceptibility of Indians to weight-related health problems, reduced the body-mass-index criteria for the diagnosis of overweight, and obesity in Indians to 23 and 25 kg/m 2, respectively. Data indicate that 15% of the Indian population has obesity. The rise in the prevalence of overweight and obesity in many lower- and middle-income countries in the Asia-Pacific region is regarded as a negative consequence of the economic development.
Arguing that obesity results from overindulgence of food or lack of physical activity is an oversimplification. Although diet is generally believed to be important in weight control and the effects of physical activity are generally modest. From the time of Dunbar and Henbest  and Alexander  to the development of the biopsychosocial model, role of psychological factors in physical illness have been well researched and acknowledged. Among the numerous efforts invested on obesity research, some determinants of obesity have been identified at both macro and micro levels, ranging from biological, behavioral factors to socioeconomic, and contextual factors.
Eating can be a form of emotion regulation, the inability to resist cravings contributes to binge eating, whereas self-discipline is required to exercise regularly. Specific behavioral variables such as body image, self-esteem, self-concept, personality traits, etc., along with cognitive and emotional correlates contribute to major preventable causes of global disease burden, including obesity.
Now being considered an important topic under behavioral medicine, behavioral determinants of obesity are thought to be conditioned by genetic and social factors. Those are believed to be important proximate factors in obesity and are taken as the pathway of distal social determinants in affecting the obesity outcome.
This line of evidence suggests that body weight is, in part, a reflection of the processes underlying individual's characteristic ways of processing self-related information in the context of other individuals and environmental factors.
The studies have found that age, ethnicity, sex, marital status, and educational level  are factors influencing overweight and obesity, in adults  as well as in children and adolescents (Wang and Zhang, 2006).
However, published research work on the psychosocial components in relation to obesity in Indian adults is sparse. This study is an attempt to probe into the issue. The selected variables of the study are as follows.
Self-concept refers to a set of self-identities and self-schemas that, together, form the person we perceive ourselves to be. The studies on self-concept in relation with obesity mostly comprised children and adolescents sample in American-African, Chinese, and Indian population. Body-image studies among adults are commonly found, but there is dearth of studies concerning self-concept of adult obese individuals.
A study by Granich et al. revealed that less supportive families can show little concern for the level of sedentary activities and has significant consequences-one being weight gain and asthma.
Reviews point to the importance of the interaction of the social environment (parents), social ties with parents, overall family environment  in self-regulation of weight-related behaviors in children, and adolescents. Baturka et al. found that the women aged 21–47 years felt a strong cultural pressure to be self-accepting and that having a larger body was a norm encouraged by their family members and significant others.
Following the WHO's definition of mental health, well-being can be conceptualized as a state where an individual can utilize his or her potentials optimally, can cope effectively, and can put forward some implications of work. Increased BMI has been shown to be associated with reduced overall health-related quality of life  and state of well-being. The studies found obese women are more adversely affected than men in terms of depression as well as anxiety, whereas obesity is protective against depression in men while there was no association in women.
From the above discussion, it is evident that the need to study aspects of obesity is becoming relevant, encompassing various biological, psychological, and social-contextual variables.
The specific objectives of the present study are as follows:
- To assess and compare between obese and nonobese adults along the dimensions of self-concept, family environment, and general well-being
- To compare between male and female obese adults along the dimensions of self-concept, family environment, and general well-being
- To explore the nature of the association between BMI and selected variables of the study.
| Subjects and Methods|| |
A sample of sixty individuals within the age group 21–50 years (mean = 25.73 ± 2.86), having minimum 8 years of formal education, Indian citizens, not suffering from any organic disease, endocrinological disorder (thyroidism and Cushing syndrome), neurological disorder, terminal illness, mental retardation, and psychiatric disorders were selected using purposive sampling method. They were classified into obese (BMI ≥25 kg/m 2) and nonobese groups on the basis of BMI, with thirty individuals in each group. The two groups were matched in terms of age, sex, and educational qualification.
The study followed cross-sectional hospital-based study design using purposive sampling method.
The variables under investigation were - self-concept, family environment, and general well-being.
Semi-structured sociodemographic datasheet
This was used to collect the background information about the participants such as the name, address, age, sex, educational qualification, marital status, occupation, family type, family income, current height and weight, health status, and family history of endocrinological disorders.
This inventory consists 64 items (adjectives) related to 10 content categories (social, emotional, physical, cognitive, esthetic, political, job-related, self-confidence, self-concept related to beliefs and traditions, and self-concept related to personality traits) of self were arranged randomly. Summation of all items would give the measure of composite self-concept. A higher score indicates positive association with good self-concept. The reliability coefficients for different dimensions as well as for the composite self-concept range between 0.58 and 0.82. The significant correlation coefficient between the dimensions of self-concept, and between composite score and dimensions (P < 0.001) indicates satisfactorily high validity of the inventory.
Family environment scale
This 69-item scale is based on the Family Environment Scale by Moss. There are three dimensions, each containing a few subscales: Relationship dimension (cohesion, expressiveness, conflict, acceptance, and caring), personal growth (independence and active recreational orientation), system maintenance (organization and control). Higher score represents greater orientation in each subscale except “conflict” subscale. The overall reliability coefficient of the scale is 0.95.
General Health Questionnaire-28
This 28-item questionnaire was used as a screening instrument for psychiatric disorder in nonclinical populations. This 28-item version has four subscales – somatic symptoms, anxiety and insomnia, social dysfunction, and severe depression. These subscale measures provide more specific domains of psychopathology or “caseness”. Each of the items has four response alternatives. The split-half reliability is 0.97. It is taken as a measure of well-being in this study.
Participants meeting inclusion criteria were first interviewed followed by an initial assessment of height, weight, and calculation of BMI using the formula: Weight in kilograms divided by the square of height in meters (kg/m 2).
Individuals' whose BMI ≥25 kg/m 2 and whose age and education level matched with the inclusion criteria were further inquired. They were informed about the research purpose, followed by taking informed consent from them. Maintenance of confidentiality of information was assured.
The sociodemographic details of the individuals were then collected using sociodemographic datasheet. Previous medical history and medical report were clarified and checked to rule out the presence of organic disease, endocrinological disorders, (thyroidism, diabetes, Cushing syndrome), and pituitary malfunctions and other secondary obesity. If in doubt, physicians' help was sought to fulfill the study criteria. Assessment of both groups was done using Self-Concept Inventory, Family Environment Scale, and General Health Questionnaire-28 (GHQ-28). Important to note that in this study, the GHQ-28 total and domain scores were analyzed for the obese group and thus were taken as the measure of their status of well-being. Individuals who scored <4 in GHQ, whose BMI was <25 kg/m 2 and who met the other inclusion criteria were included in the nonobese group and then assessed with the remaining tools following the same procedure as applicable for the study group.
Statistical analyses were done using IBM SPSS version 20.0 (International Business Machine, New York). Statistical analyses included descriptive statistics mean and standard deviations. Comparison between the two groups in terms of different variables was done using Student's t-test, Chi-square test. Correlational analysis was also done for the selected group according to the objectives of the study.
| Results|| |
The results of the study have been shown in the following tables:
[Table 1] indicates that the two groups differ significantly from each other with respect to weight (t = 7.05; P < 0.01) and BMI (t = 11.72; P < 0.01).
|Table 1: Differences between obese and nonobese groups in terms of age, height, weight, and body mass index|
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[Table 2] shows the differences between obese and nonobese groups in terms of sociodemographic variables. There exists a significant difference between obese and nonobese individuals with respect to family history of the endocrinological disorder (χ2 = 4.59; P < 0.05). However, these two groups did not differ in terms of sex, educational qualification, marital status, occupation, and family type.
|Table 2: Differences between obese and nonobese groups in terms of sociodemographic variables|
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[Table 3] shows the comparison between obese and nonobese group according to self-concept.
|Table 3: Comparison between obese and nonobese group according to self-concept|
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It is observed that obese and nonobese group differ significantly with respect to “emotional self-concept” (t = 2.73; P = 0.01), “cognitive self-concept” (t = 2.31; P < 0.05), “political self-concept” (t = 2.32; P < 0.05), “job-related self-concept” (t = 2.71; P = 0.01), and “self-concept related to beliefs and traditions” (t = 3.42; P < 0.01). As higher score in self-concept inventory (SCI) is indicative of good self-concept in respective domains, lesser mean in “emotional self-concept” (mean = 26.17; standard deviation [SD] = 3.26), and “self-concept related to beliefs and tradition” (mean = 13.03; SD = 2.33) in obese group than those of in nonobese group (mean = 29.67; SD = 6.23 and mean = 15.03; SD = 2.20, respectively), indicates that obese group tends to be poorer than the nonobese group in these domains. On the other hand, greater mean in the domains of “cognitive self-concept” (mean = 17.43; SD = 2.98), “political self-concept” (mean = 17.27; SD = 3.22), and “job related self-concept” (mean = 23.13; SD = 3.39) than those of in nonobese group (mean = 15.50, SD = 3.47; mean = 15.40, SD = 3.01; mean = 20.57, SD = 3.92, respectively) implies better self-concept in obese individuals as compared to the nonobese ones in these domains [Table 3].
Gender-wise male-female comparison in obese group reveals that there exist significant differences between male and female in terms of “emotional self-concept” (t = 2.21; P < 0.05) and “physical self-concept” (t = 2.74; P = 0.01). Greater mean (mean = 27.40, SD = 2.72) in case of female obese group as compared to the male obese group (mean = 24.93, SD = 3.37) with respect to “emotional self-concept” implies that the former has better emotional self-concept than the latter. However, female obese individuals are shown to have poor “physical self-concept” (mean = 8.87, SD = 2.07) than male obese group (mean = 11.40, SD = 2.92) [Table 4].
|Table 4: Comparison between male and female obese individuals according to self-concept|
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[Table 5] shows there exists no significant difference between obese and nonobese group along the dimensions of family environment scale. However, the subscale of active recreational orientation is shown to have a tendency toward significance indicating poorer active recreational orientation than nonobese group [Table 5].
|Table 5: Comparison between obese and nonobese group according to family environment subscales|
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In obese group, male and female individuals have been found not to vary along the family environment dimensions [Table 6].
|Table 6: Comparison between male and female obese individuals with respect to family environment subscales|
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[Table 7] shows that the obese group differs significantly as compared to the nonobese group in terms of general well-being (t = 5.64; P < 0.00) and its various domains of somatic symptoms (t = 3.95; P < 0.00), anxiety and insomnia (t = 8.26; P < 0.00), social dysfunction (t = 3.34; P < 0.00), and severe depression (t = 2.19; P < 0.05). The obese group has lesser well-being (mean = 6.06, SD = 5.52), more severity of depression (mean = 0.73, SD = 1.52), greater social dysfunction (mean = 1.36, SD = 1.99), greater anxiety and insomnia (mean = 2.46, SD = 1.63), and more somatic symptoms (mean = 1.46, SD = 2.02) as compared to nonobese group (mean = 0.33, SD = 0.66; mean = 0.10, SD = 0.40; mean = 0.13, SD = 0.34; mean = 0.00, SD = 0.00; mean = 0.00, SD = 0.00, respectively).
|Table 7: Comparison between obese and nonobese group with respect to General Health Questionnaire subscales|
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[Table 8] shows that the male and female obese individuals significantly differ in the domains of severe depression (t = 2.95, P < 0.01*) and somatic symptoms (t = 5.73, P < 0.00**). The female obese individuals have more severity of depression (mean = 1.46. SD = 1.92) and greater somatic symptoms (mean = 2.93, SD = 1.98) as compared to the male obese individuals (mean = 0.00, SD = 0.00; mean = 0.00, SD = 0.00, respectively).
|Table 8: Comparison between male and female obese individuals with respect to General Health Questionnaire subscales|
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[Table 9] Correlation analyses of BMI with domains of self-concept, family environment, and general well-being, as revealed from [Table 9], reflect that in obese group, BMI is negatively and significantly correlated with social self-concept (r = –0.46; P = 0.01), cognitive self-concept (r = –0.44; P < 0.05), political self-concept (r = –0.38; P < 0.05), self-confidence (r = –0.40; P < 0.05), and self-concept related to personality traits (r = –0.37; P = 0.05). As according to SCI, higher score is indicative of good self-concept significant negative correlations imply that higher BMI is associated with poor self-concept in the respective domains in obese individuals. No other variables have found to share a significant association with BMI in this group.
|Table 9: Correlation of body mass index with other variables in obese group|
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| Discussion|| |
According to the objectives of this study, statistical analysis of the data attempted to probe into the fact whether there exists any significant difference between obese and nonobese groups as well as any gender-wise difference in the obese group and to explore the correlation between BMI and the selected variables of the study. Some findings of the study have brought out certain basic differences.
In this study, the total sample comprised 60 individuals within the age group 21–50 years (mean = 25.73 ± 2.86). They were classified into obese and nonobese groups on the basis of measures of BMI. As obvious, the groups differed significantly in terms of body weight and BMI but were matched in terms of age and sex. Findings of comparison between the two groups along relevant sociodemographic variables viz., education, occupation, marital status, family types, etc., denote no significant difference.
In addition, the study shows a significant difference between obese and nonobese individuals with respect to family history of endocrinological disorders which is in accordance with earlier findings and provides support in favor of genetic inheritance of and predisposition to obesity.
Obesity and self-concept
The self-concept is an organized, consistent conceptual gestalt composed of perceptions of the characteristics of “I” or “Me” to others and to various aspects of life, together with the values attached to these perceptions. The current findings indicate that obese individuals have significantly poorer emotional self-concept as compared to the nonobese ones which may signify obese individuals' vulnerability to develop affective disturbances, dysphoria, and even depression. Poor “self-concept related to beliefs and traditions” of obese individuals in comparison with their nonobese counterparts, may imply dysfunctional core of self-concept in association with social and cultural aspects of self as governed by contextual experiences. In fact, just being associated with someone who is overweight can lead to negative evaluations. As such, body weight contributes to how we understand ourselves, how we see others, and how others see us.
Although the two groups have shown to differ significantly in terms of “cognitive self-concept,” the obese group scores higher in this dimension than the nonobese group, thus implying their potential ability to process self-related information, and interpretations drawn from environmental cues in an effective manner. This may serve as a good prognostic indicator in case of obesity-related interventions. In addition, this finding when considered together with poor emotional self-concept in obese individuals may provide us with the explanation how thinking and behavior have become distorted to be congruent with emotional states.
The overall obese group is also found to have better 'political self-concept' and 'job-related self-concept' as compared to their nonobese counterparts. This bears a connotation for the sedentary lifestyle, spending greater time in workplace which mostly involves less physical activity in contrast with greater availability of high-calorie food. Moreover, social, cultural traditions are by no means fragile issues. Those culminate propensity to adhere to the traditional lifestyle practices, often results in weight gain and obesity. In contrary, author's experience of regular social affairs and the narratives patients give at the time of explaining their problems in the clinic, prompt to report the contradiction between their access of weight loss interventions and continuing with the same lifestyle pattern prevailed before they opted intervention.
Poor “physical self-concept” in female obese individuals as compared to their male counterparts further indicates the role of negative self-appraisal and the importance of discriminatory societal attitude toward physical appearance of females., This finding may serve as evidence for shift in traditional concepts related to obesity as history suggests that overweight women symbolizes society's wealth and well-being in many parts of the world, including East Asian Civilization where obesity symbolizes prosperity and social status.
In addition, obese females are found to have better “emotional self-concept” than obese males. This finding is contradicted by the studies showing association between obesity as protective factor against depression in men while there was no association in women.
Further exploration with correlational analysis indicates that the higher BMI, the poor is the self-concept in the domains of social self-concept, cognitive self-concept, political self-concept, self-confidence and self-concept related to personality traits in obese individuals.
However, available literature would not provide any direction in explaining these aspects. These domains, thus, need further investigation.
Obesity and family environment
From this study, no significant differences between obese and nonobese group have been found along the family environment dimensions, namely, relationship, personal growth, and system maintenance. However, the subscale of active recreational orientation, under personal growth dimension, is shown to have a tendency toward significance indicating poorer active recreational orientation than nonobese group. Since the finding is not statistically significant, further comment on this cannot be made. Male and female obese individuals also did not differ significantly along these dimensions.
The experience of the researcher during interview and data collection may be narrated in this context. During data collection, a substantial number of female obese individuals report unsupportive, discouraging family environment, and interpersonal dispute with significant others in the family, but that is not reflected significant in the statistical analyses. Further probe in this domain with a different approach is thus recommended.
Obesity and general well-being
Following the purpose of using GHQ-28, the present study used this particular tool for screening the nonobese group. As literature indicates that the physical and emotional well-being is not maintained in obesity, evidently it was hypothesized that there would be a significant difference between the obese and nonobese group. According to the presumption, results unravel that obese group has lesser well-being, more somatic symptoms, greater anxiety and insomnia, and more severity of depression as compared to nonobese group. Particular interest lies in the gender-wise comparison in the obese group along GHQ domains. Results reveal that female obese individuals have greater somatic symptoms and more severity of depression as compared to their male counterparts. As in case of depression, the symptoms are not restricted to the affective domain but prominently related to poor self-image, lowered self-esteem as well as with greater degree of perceived stress and over-eating behavior, this finding is supported by existing body of literature indicating obese individuals', especially females' vulnerability to develop affective disturbances, dysphoria. However, interesting findings emerge: As female obese individuals have been found to have better “emotional self-concept” than obese males, their greater vulnerability of depression in the GHQ-28 tends to signify ineffective employment of coping skills to hold back the dysregulation of emotions otherwise, despite having better self-schemes related to emotions as compared to their male counterparts. This further indicates skills training can be one of the strategies of obesity intervention. Moreover, body image preoccupation is a well-researched topic in the context of obesity. However, exploring the nature and severity of other somatic concerns have not found to be documented. In general, females are found to have greater somatic complaints than male; this study unfolds that obese females have greater somatic symptoms such as feeling of physical weakness, headache, etc., than obese males. However, caution should be maintained as GHQ provides the “caseness;” therefore, these findings provide a preliminary database about the status of psychiatric vulnerabilities in obese individuals that hinder their general well-being.
However, the study is not free of limitations. The present sample was small in size. With larger samples, more subtle changes in mean scores can be detected over time leading to more precise comparison. In addition, here, the individuals are broadly assigned into two groups, namely, obese and nonobese, including overweight in the nonobese group and BMI was taken as the only demarcation between the two groups. Classifying overweight individuals in a separate category apart from the nonobese group and using other parameters for diagnosing obesity cases might have led toward more precision. Moreover, sociocontextual aspect needs more detail exploration. Assessment of the domains of the GHQ-28 with separate specialized tools is implied.
Acknowledging these limitations, it can be highlighted from the findings that the present study would aid the treatment process of obesity and aid health professionals to plan intervention incorporating the biopsychosocial aspects so that complexities of the obesity management can be effectively facilitated.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Haslam DW, James WP. Obesity. Lancet 2005;1:366.
World Health Organization. Global Tuberculosis Control: WHO Report 2010. Geneva: World Health Organization; 2010.
Centers for Disease Control and Prevention. Sexually transmitted diseases treatment guidelines, 2010. Ann Emerg Med 2011;58:67-8.
Misra A, Chowbey P, Makkar BM, Vikram NK, Wasir JS, Chadha D, et al.
Consensus statement for diagnosis of obesity, abdominal obesity and the metabolic syndrome for Asian Indians and recommendations for physical activity, medical and surgical management. J Assoc Physicians India 2009;57:163-70.
Asia Pacific Cohort Studies Collaboration. The burden of overweight and obesity in the Asia-Pacific region. Obes Rev 2007;8:191-6.
Dunbar CO, Henbest LG. The fusilinid genera fusulina, fusulinella, and Wedekindella. Am J Sci 1930;119:357-64.
Alexander F. Emotional Factors in Essential Hypertension: Presentation of a Tentative Hypothesis. Psychosomatic Med 1939;1:173-9.
Engel GL. The need for a new medical model: A challenge for biomedicine. Science 1977;196:129-36.
Evers C, Marijn Stok F, de Ridder DT. Feeding your feelings: Emotion regulation strategies and emotional eating. Pers Soc Psychol Bull 2010;36:792-804.
Rush CC, Becker SJ, Curry JF. Personality factors and styles among college students who binge eat and drink. Psychol Addict Behav 2009;23:140-5.
Shah B. Manual for Self-concept Inventory (Adults). Agra, India: Agra Psychological Research Cell; 1986.
Bhatia NK, Chadha BS. Manual for Family Environment Scale. Luckhnow: Ankur Psychological Agency; 1993.
Goldberg DP, Hillier VF. A scaled version of the General Health Questionnaire. Psychol Med 1979;9:139-45.
Rogers CR. A theory of therapy, personality, and interpersonal relationships: As developed in the client-centered framework. New York: Guilford Press,1959. p. 188.
Hoyt AL, Rhodes RE, Hausenblas HA, Giacobbi PR. Integrating five-factor model facet-level traits with the theory of planned behavior and exercise. Psychol Sport Exerc 2009;10:565-72.
Wardle J, Griffith J. Socioeconomic status and weight control practices in British adults. J Epidemiol Community Health 2001;55:185-90.
Ogden J, Chanana A. Explaining the effect of ethnic group on weight concern: Finding a role for family values. Int J Obes Relat Metab Disord 1998;22:641-7.
Wakslak CJ, Nussbaum S, Liberman N, Trope Y. Representations of the self in the near and distant future. J Pers Soc Psychol 2008;95:757-73.
Witherspoon D, Latta L, Wang Y, Black MM. Do depression, self-esteem, body-esteem, and eating attitudes vary by BMI among African American adolescents? J Pediatr Psychol 2013;38:1112-20.
Granich J, Rosenberg M, Knuiman M, Timperio A. Understanding children's sedentary behaviour: A qualitative study of the family home environment. Health Educ Res 2010;25:199-210.
Frankel LA, Hughes SO, O'Connor TM, Power TG, Fisher JO, Hazen NL. Parental influences on children's self-regulation of energy intake: Insights from developmental literature on emotion regulation. J Obes 2012;2012:327259.
Crossman A, Anne Sullivan D, Benin M. The family environment and American adolescents' risk of obesity as young adults. Soc Sci Med 2006;63:2255-67.
Gesell SB, Barkin SL, Valente TW. Social network diagnostics: A tool for monitoring group interventions. Implement Sci 2013;8:116.
Baturka N, Hornsby PP, Schorling JB. Clinical implications of body image among rural African-American women. J Gen Intern Med 2000;15:235-41.
Ul-Haq Z, Mackay DF, Fenwick E, Pell JP. Association between body mass index and mental health among Scottish adult population: A cross-sectional study of 37,272 participants. Psychol Med 2014;44:2231-40.
Luppino FS, de Wit LM, Bouvy PF, Stijnen T, Cuijpers P, Penninx BW, et al.
Overweight, obesity, and depression: A systematic review and meta-analysis of longitudinal studies. Arch Gen Psychiatry 2010;67:220-9.
Linehan MM. Skills Training Manual for Treating Borderline Personality Disorder. New York: Guilford Press; 1993.
Wade TJ, DiMaria C. Weight halo effects: Individual differences in perceived life success as a function of women's race and weight. Sex Roles 2003;48:461-5.
Palinkas LA, Wingard DL, Barrett-Connor E. Depressive symptoms in overweight and obese older adults: A test of the “jolly fat” hypothesis. J Psychosom Res 1996;40:59-66.
Jorm AF, Korten AE, Christensen H, Jacomb PA, Rodgers B, Parslow RA. Association of obesity with anxiety, depression and emotional well-being: A community survey. Aust N
Z J Public Health 2003;27:434-40.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8], [Table 9]